Download Basic Environmental Sciences

Basic Environmental Sciences
What is Environmental Sciences
What is Environmental Sciences
• The study of how humans interact with their
environment
• Our environment is everything that
surrounds us, both natural and man-made.
Environment: the total of our
surroundings
• All the things around us with which we
interact:
• Living things
• Animals, plants, forests, fungi, etc.
• Nonliving things
• Continents, oceans, clouds, soil, rocks
• Our built environment
• Buildings, human-created living centers, traffic
• Social relationships and institutions
Environmental science: how does the
natural world work?
• An
interdisciplinary
field
–Natural sciences:
information
about the world
–Social sciences:
values and
human behavior,
politics, economy,
etc.
What is Ecology?
• Origin of word ecology
• Greek origin
• OIKOS = household
• LOGOS = study of…
• Study of the “house/environment” in which
we live.
Ecology is study of interactions
between
• non-living components in the environment…
– light
– water
– wind
– nutrients in soil
– heat
– solar radiation
– atmosphere, etc.
AND…
• Living organisms…
– Plants
– Animals
– microorganisms in soil, etc.
ECOLOGY:
Levels of Organization
Types of Ecology
Ecology research types
-
Autoecology: species connections with their ecological habitats.
Methods: field and laboratory researches join to other ciences (
(life sciences, ecophysiology, ethology)
-
Demoecology: research the interactions between populations and
their connections with the environment. Methods: field study,
statistica, mathematic modells. Works with population genetics
-
Ecology above populations: research the ecosystem, descriptive
and canonical. System analyzer. Nem Ecology (Odum, 1971)
Biotic and abiotic measures
Biotic factors
- species genetical variabilty
- species looks variability
- species capacity for living ( vitality, growing, sex, race) (
Abiotic factors
- light
- temperature
- transparency / secchi depth
- conductivity
- humidity
- pH
- oxigen content
Research questions
Hypotesis
Predictions
Previous
researches
Parameter selection
Data recording methods
Data collecting
Data analyses
Results
Précsényi István: Alapvető kutatástervezési, statisztikati,…. Debrecen, 1995
The „ test „ research, previous researches
• We have some idea but we need more informations:
–
–
–
–
About the methods
The errors of the methods
The effect of the experiment
The costs and complications
„Demonstrative ” research
• We have previously results from the test
research
•
•
•
•
•
The aims
The populations
The parameters
The evaluation methods
The quality and the quantity of results
Reliability of the datas
• Every data must be recorded
• Every unintended property must be recorded
• Identified the „wrong data”, delate?
• Outlier data, (no mistake or error but the result hang
out
• Verify or controll the recorded data
Empirical and ideal data size
• The empirical data size must be large
• More sample – more results
• This the m , the size of m contolled the time and money
• The numbers of paremeters give us the samling number, this is „n”
• The ideal sampling size is n x m, the product of the sampling
stations and the parameters
Systematic errors
– randomization
• Random sampling
• Types of randomization
– simply
– Using blocks
– Stratified
– blind, double blind test
Simple random sampling
• All sampling station has the same chance for
sampling
• Parts of the samples are choosed
independently
„stratified random” sampling
• We used when the sampling area could divisible due to
exterior rules (depth)
• Each levels we could use simply random sampling
Systematic random sampling
• The first sampling station is random, but the others use
rules.
• The sampling interval is the distance (space or time)
Semi systematic random sampling
• We use square blocks, in the square blocks we use
simple random sampling
The lain square
• Name from Euler Leonhard
Definition: the n × n dimension square is a square matrix where the samlings never
return, the parts of the matrix permutate.
Research
• Now we have samling system
• We have samplig sizes
• We have variables
– Main variables
– Supplementary variables
– Relationship between variables
– Categories and scales
Scales types
Intervallum
Relation
Nominal
ordinal
Skála
Definíció
Példák
Nominális
1.kvalitatív,
nevekből áll
2.nincs rangsor
ivar,
Ordinális
1.kvalitatív,
rangsor lehetséges
2.értékek közti távolság
tetszőleges
agresszivitás:
1.kvantitatív,
hőmérséklet
Intervallum
Arány
rangsor, értékek
közti különbség mutatja a
távolságot
2.önkényes nulla pont
3.arányok nem értelmezhetők
1.kvantitatív, rangsor, értékek
közti intervallum mutatja a
távolságot
2.valódi nullapont
3.arányok értelmezhetőek
betegség
erős, közepes,
gyenge
(C), IQ
testsúly,
magasság, életkor